Expanding the spectrum of cancer targets by predicting individual gene fusions

We developed EasyFuse, a computational machine learning pipeline that detects cancer-specific gene fusions with superior performance over existing tools. Individual gene fusions exhibit a high frequency of pre-established CD4(+) and CD8(+) T-cell responses and thus represent a previously untapped source of neo-antigens that can be exploited for personalized immunotherapies.